The chromosome-scale reference genome of black pepper provides insight into piperine biosynthesis

Black pepper (Piper nigrum), dubbed the ‘King of Spices’ and ‘Black Gold’, is one of the most widely used spices. Here, we present its reference genome assembly by integrating PacBio, 10x Chromium, BioNano DLS optical mapping, and Hi-C mapping technologies. The 761.2 Mb sequences (45 scaffolds with an N50 of 29.8 Mb) are assembled into 26 pseudochromosomes. A phylogenomic analysis of representative plant genomes places magnoliids as sister to the monocots-eudicots clade and indicates that black pepper has diverged from the shared Laurales-Magnoliales lineage approximately 180 million years ago. Comparative genomic analyses reveal specific gene expansions in the glycosyltransferase, cytochrome P450, shikimate hydroxycinnamoyl transferase, lysine decarboxylase, and acyltransferase gene families. Comparative transcriptomic analyses disclose berry-specific upregulated expression in representative genes in each of these gene families. These data provide an evolutionary perspective and shed light on the metabolic processes relevant to the molecular basis of species-specific piperine biosynthesis

The Clinical and Economic Impact of Point-of-Care CD4 Testing in Mozambique and Other Resource-Limited Settings: A Cost-Effectiveness Analysis

Background: Point-of-care CD4 tests at HIV diagnosis could improve linkage to care in resource-limited settings. Our objective is to evaluate the clinical and economic impact of point-of-care CD4 tests compared to laboratory-based tests in Mozambique. Methods and Findings: We use a validated model of HIV testing, linkage, and treatment (CEPAC-International) to examine two strategies of immunological staging in Mozambique: (1) laboratory-based CD4 testing (LAB-CD4) and (2) point-of-care CD4 testing (POC-CD4). Model outcomes include 5-y survival, life expectancy, lifetime costs, and incremental cost-effectiveness ratios (ICERs). Input parameters include linkage to care (LAB-CD4, 34%; POC-CD4, 61%), probability of correctly detecting antiretroviral therapy (ART) eligibility (sensitivity: LAB-CD4, 100%; POC-CD4, 90%) or ART ineligibility (specificity: LAB-CD4, 100%; POC-CD4, 85%), and test cost (LAB-CD4, US$10; POC-CD4, US$24). In sensitivity analyses, we vary POC-CD4-specific parameters, as well as cohort and setting parameters to reflect a range of scenarios in sub-Saharan Africa. We consider ICERs less than three times the per capita gross domestic product in Mozambique (US$570) to be cost-effective, and ICERs less than one times the per capita gross domestic product in Mozambique to be very cost-effective. Projected 5-y survival in HIV-infected persons with LAB-CD4 is 60.9$2,440 (95% CI, US$2,440–US$2,450) and increase with POC-CD4 to 10.3 y (95% CI, 10.3–10.3 y) and US$2,800 (95$2,790–US$2,800); the ICER of POC-CD4 compared to LAB-CD4 is US$500/year of life saved (YLS) (95% CI, US$480–US$520/YLS). POC-CD4 improves clinical outcomes and remains near the very cost-effective threshold in sensitivity analyses, even if point-of-care CD4 tests have lower sensitivity/specificity and higher cost than published values. In other resource-limited settings with fewer opportunities to access care, POC-CD4 has a greater impact on clinical outcomes and remains cost-effective compared to LAB-CD4. Limitations of the analysis include the uncertainty around input parameters, which is examined in sensitivity analyses. The potential added benefits due to decreased transmission are excluded; their inclusion would likely further increase the value of POC-CD4 compared to LAB-CD4. Conclusions: POC-CD4 at the time of HIV diagnosis could improve survival and be cost-effective compared to LAB-CD4 in Mozambique, if it improves linkage to care. POC-CD4 could have the greatest impact on mortality in settings where resources for HIV testing and linkage are most limited. Please see later in the article for the Editors' Summar

The clinical and economic impact of point-of-care CD4 testing in Mozambique and other resource-limited settings: a cost-effectiveness analysis

Emily Hyle and colleagues conduct a cost-effectiveness analysis to estimate the clinical and economic impact of point-of-care CD4 testing compared to laboratory-based tests in Mozambique. Please see later in the article for the Editors' Summar

Evaluating operational specifications of point-of-care diagnostic tests: a standardized scorecard.

The expansion of HIV antiretroviral therapy into decentralized rural settings will increasingly require simple point-of-care (POC) diagnostic tests that can be used without laboratory infrastructure and technical skills. New POC test devices are becoming available but decisions around which technologies to deploy may be biased without systematic assessment of their suitability for decentralized healthcare settings. To address this, we developed a standardized, quantitative scorecard tool to objectively evaluate the operational characteristics of POC diagnostic devices. The tool scores devices on a scale of 1-5 across 30 weighted characteristics such as ease of use, quality control, electrical requirements, shelf life, portability, cost and service, and provides a cumulative score that ranks products against a set of ideal POC characteristics. The scorecard was tested on 19 devices for POC CD4 T-lymphocyte cell counting, clinical chemistry or hematology testing. Single and multi-parameter devices were assessed in each of test categories. The scores across all devices ranged from 2.78 to 4.40 out of 5. The tool effectively ranked devices within each category (p<0.01) except the CD4 and multi-parameter hematology products. The tool also enabled comparison of different characteristics between products. Agreement across the four scorers for each product was high (intra-class correlation >0.80; p<0.001). Use of this tool enables the systematic evaluation of diagnostic tests to facilitate product selection and investment in appropriate technology. It is particularly relevant for countries and testing programs considering the adoption of new POC diagnostic tests

Spider-plot scores of the highest performing technologies.

<p>Spider-plot scores of the highest performing technologies.</p

Point-of-care medical diagnostic products evaluated with the scorecard.

<p>Point-of-care medical diagnostic products evaluated with the scorecard.</p

Diagnostic technology scorecard assessment criteria with scoring thresholds and weightings.

<p>Diagnostic technology scorecard assessment criteria with scoring thresholds and weightings.</p

The chromosome-scale reference genome of black pepper provides insight into piperine biosynthesis

Black pepper (Piper nigrum), dubbed the ‘King of Spices’ and ‘Black Gold’, is one of the most widely used spices. Here, we present its reference genome assembly by integrating PacBio, 10x Chromium, BioNano DLS optical mapping, and Hi-C mapping technologies. The 761.2 Mb sequences (45 scaffolds with an N50 of 29.8 Mb) are assembled into 26 pseudochromosomes. A phylogenomic analysis of representative plant genomes places magnoliids as sister to the monocots-eudicots clade and indicates that black pepper has diverged from the shared Laurales-Magnoliales lineage approximately 180 million years ago. Comparative genomic analyses reveal specific gene expansions in the glycosyltransferase, cytochrome P450, shikimate hydroxycinnamoyl transferase, lysine decarboxylase, and acyltransferase gene families. Comparative transcriptomic analyses disclose berry-specific upregulated expression in representative genes in each of these gene families. These data provide an evolutionary perspective and shed light on the metabolic processes relevant to the molecular basis of species-specific piperine biosynthesis.This article is published as Hu, Lisong, Zhongping Xu, Maojun Wang, Rui Fan, Daojun Yuan, Baoduo Wu, Huasong Wu et al. "The chromosome-scale reference genome of black pepper provides insight into piperine biosynthesis." Nature Communications 10 (2019): 4702. doi: 10.1038/s41467-019-12607-6.</p

Score, rank and inter-class correlation of point-of-care technologies assessed with the scorecard.

*<p>all p-values<0.0001.</p